__sizeof__() method returns the size of the object in bytes. The
sys.getsizeof() method internally call’s
__sizeof__() and adds some additional byte overhead, e.g., for garbage collection.
The following code snippet creates a list object
x with three integers and measures its size in bytes (104) using the
x.__sizeof__() method call.
It then measures the size with overhead using
>>> import sys >>> x = [1, 2, 3] >>> x.__sizeof__() 104 >>> sys.getsizeof(x) 120
Let’s make the list much larger to measure if it has any impact on the size in bytes.
>>> import sys >>> x = list(range(10000)) >>> x.__sizeof__() 80040 >>> sys.getsizeof(x) 80056
This list is built using the
range() function. It has 10000 integers, each needing 8 bytes with a constant overhead of 40 bytes for the list structure, the
x.__sizeof__() method call results in 10000 * 8 + 40 = 80040 bytes.
You can see that in both cases, the
sys.getsizeof(x) has 16 more bytes than
x.__sizeof__() which seems to be the overhead on my particular machine for this particular example.
You can override the
__sizeof__() method for your own custom data type by defining the
__sizeof__() method with one argument
self (that is passed automatically by Python).
import sys class Data: def __sizeof__(self): return 42 x = Data() print(x.__sizeof__())
__sizeof__() method returns the integer 42 that was returned by us—not the number of bytes.
Let’s call the
sys.getsizeof() method to see if the difference is 16 bytes for the GC overhead!
import sys class Data: def __sizeof__(self): return 42 x = Data() print(x.__sizeof__()) # 42 print(sys.getsizeof(x)) # 58
Where to Go From Here?
Enough theory. Let’s get some practice!
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While working as a researcher in distributed systems, Dr. Christian Mayer found his love for teaching computer science students.
To help students reach higher levels of Python success, he founded the programming education website Finxter.com that has taught exponential skills to millions of coders worldwide. He’s the author of the best-selling programming books Python One-Liners (NoStarch 2020), The Art of Clean Code (NoStarch 2022), and The Book of Dash (NoStarch 2022). Chris also coauthored the Coffee Break Python series of self-published books. He’s a computer science enthusiast, freelancer, and owner of one of the top 10 largest Python blogs worldwide.
His passions are writing, reading, and coding. But his greatest passion is to serve aspiring coders through Finxter and help them to boost their skills. You can join his free email academy here.